{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello World\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\goomhoom'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {i:np.random.randn() for i in range(7)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 0.2573662848438335,\n",
       " 1: -0.43626307848375856,\n",
       " 2: 0.22037246444856265,\n",
       " 3: 0.8216808681040964,\n",
       " 4: 1.3429776557272914,\n",
       " 5: -0.18024650227280228,\n",
       " 6: 0.8635806875785843}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.random import randn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {i:randn() for i in range(7)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 0.12940648617727327, 1: 0.48304040691449857, 2: 0.6183676788436143, 3: -0.0035102445687102204, 4: 0.4046556412561957, 5: 0.354218224771292, 6: -0.3338724586305887}\n"
     ]
    }
   ],
   "source": [
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\goomhoom'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "path='data.txt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"tz\": null}\\n'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "open(path).readline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "path='data.txt'\n",
    "records=[json.loads(i) for i in open(path)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'tz': None}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "records[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "records[0]['tz']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(records[0]['tz'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "an_apple=27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "an_example=42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "an_apple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "b=[1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fun_with_keywords(abra=1,abbra=2,abbbra=3):\n",
    "    return abra,abbra,abbbra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 2, 100)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fun_with_keywords(abbbra=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "b=[1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-31-5791a7f58025>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-31-5791a7f58025>\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m    b ?\u001b[0m\n\u001b[1;37m      ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "b ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "b?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "print?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_numbers(a,b):\n",
    "    '''\n",
    "    Add two number together\n",
    "    \n",
    "    Returns \n",
    "    _______\n",
    "    the_sum:type of arguments\n",
    "    '''\n",
    "    return a+b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "add_numbers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "add_numbers??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "print??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "add_numbers??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "print??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "np.*load*?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "a,b,c=5,6,7.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello world\n"
     ]
    }
   ],
   "source": [
    "%run test.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4666666666666666"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f78421e278>]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f78496ca20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(randn(50).cumsum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = [1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.append(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def append_element(some_list,element):\n",
    "    some_list.append(element)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "append_element(data,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=\"foo\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "must be str, not int",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-70-4dd8efb5fac1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;34m'5'\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: must be str, not int"
     ]
    }
   ],
   "source": [
    "'5' + 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a is <class 'float'>,b is <class 'int'>\n"
     ]
    }
   ],
   "source": [
    "print('a is {0},b is {1}'.format(type(a),type(b)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.25"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a/b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isinstance(5,int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=5;b=4.5;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isinstance(a,(int,float))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isinstance(b,(int,float))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 'foo'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function str.split>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "getattr(a,'split')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "def isiterable(obj):\n",
    "    try:\n",
    "        iter(obj)\n",
    "        return True\n",
    "    except TypeError:\n",
    "        return False\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isiterable('a string')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isiterable([1,2,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isiterable(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "import some_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "some_model.f(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "pi = some_model.PI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = some_model.g(pi,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.14159265"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "5-7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33.5"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "12+21.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "5<=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=[1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "c= list(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is not c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a == c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2^1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1^1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_list = ['f00',2,[4,5]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_list[2] = (3,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['f00', 2, (3, 4)]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_tuple=(4,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_tuple[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_tuple[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_tuple = (3,5,(4,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-116-d0d60d6f5539>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma_tuple\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "a_tuple[2] = (3,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "ival = 1232132131"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3498998033239207461551428375976877678841329742468736281"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ival**6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "fval = 7.234"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "f.val = 6.78e-5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.5"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "3/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "3//2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "a='one way of write a string'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "b='another way'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "c='''\n",
    "this is a long string\n",
    "contians multi-lines\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c.count('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 'this is a string'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'str' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-129-c01e0915bff8>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m't'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: 'str' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "a[5]='t'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = a.replace('string','long string')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is a long string'"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is a string'"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 5.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = str(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'5.6'"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.6\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = 'python'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = list(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['p', 'y', 't', 'h', 'o', 'n']"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'pyt'"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['p', 'y', 't']"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = '12\\\\34'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'12\\\\34'"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12\\34\n"
     ]
    }
   ],
   "source": [
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = r'this\\has\\no\\special\\char'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this\\\\has\\\\no\\\\special\\\\char'"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 'this is a first half \\n'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = ' and this is a second half'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is a first halfant this is a second half'"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a+b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "template = '{0:.2f} {1:s} are worth ${2:d}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'4.56 pie are worth $5'"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "template.format(4.5560,'pie',5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "val = 'good good 学习，day day up'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'good good 学习，day day up'"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_utf8 = val.encode('utf8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'good good \\xe5\\xad\\xa6\\xe4\\xb9\\xa0\\xef\\xbc\\x8cday day up'"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_utf8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bytes"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(val_utf8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'good good 学习，day day up'"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_utf8.decode('utf8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_utf16 = val.encode('utf-16')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'\\xff\\xfeg\\x00o\\x00o\\x00d\\x00 \\x00g\\x00o\\x00o\\x00d\\x00 \\x00f[`N\\x0c\\xffd\\x00a\\x00y\\x00 \\x00d\\x00a\\x00y\\x00 \\x00u\\x00p\\x00'"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_utf16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'good good 学习，day day up'"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_utf16.decode('utf16')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "bytes_val = b'this is a bytes'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'this is a bytes'"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bytes_val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "decoded = bytes_val.decode('utf8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is a bytes'"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "True and False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "True or False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = '3.14159265'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "fval = float(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.14159265"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(fval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "int(fval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bool(fval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bool(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b is not None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_maybe_multi(a,b,c=None):\n",
    "    result = a + b\n",
    "    if c is not None:\n",
    "        result = result * c\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NoneType"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime,date,time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = datetime(2019,1,1,1,1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.minute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2019, 1, 1)"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.date()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.time(1, 1, 1)"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'01/01/2019 01:01'"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.strftime('%m/%d/%Y %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2019, 1, 1, 0, 0)"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.strptime('20190101','%Y%m%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2019-01-01'"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.strftime('%F')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2019, 1, 9, 1, 0)"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.replace(day=9,minute=0,second=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2019, 1, 1, 1, 1, 1)"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_dt = datetime(2019,1,30,9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "delta = a_dt - dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.timedelta(29, 28739)"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2019, 1, 30, 9, 0)"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt+delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "a,b,c,d=5,7,8,4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Made it\n"
     ]
    }
   ],
   "source": [
    "if a<b or c>d:\n",
    "    print('Made it')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "4>3>2>1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1<a<5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 0)\n",
      "(1, 0)\n",
      "(1, 1)\n",
      "(2, 0)\n",
      "(2, 1)\n",
      "(2, 2)\n",
      "(3, 0)\n",
      "(3, 1)\n",
      "(3, 2)\n",
      "(3, 3)\n"
     ]
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    for j in range(4):\n",
    "        if j>i:\n",
    "            break\n",
    "        print((i,j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 100)"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 1,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 7,\n",
       " 8,\n",
       " 9,\n",
       " 10,\n",
       " 11,\n",
       " 12,\n",
       " 13,\n",
       " 14,\n",
       " 15,\n",
       " 16,\n",
       " 17,\n",
       " 18,\n",
       " 19,\n",
       " 20,\n",
       " 21,\n",
       " 22,\n",
       " 23,\n",
       " 24,\n",
       " 25,\n",
       " 26,\n",
       " 27,\n",
       " 28,\n",
       " 29,\n",
       " 30,\n",
       " 31,\n",
       " 32,\n",
       " 33,\n",
       " 34,\n",
       " 35,\n",
       " 36,\n",
       " 37,\n",
       " 38,\n",
       " 39,\n",
       " 40,\n",
       " 41,\n",
       " 42,\n",
       " 43,\n",
       " 44,\n",
       " 45,\n",
       " 46,\n",
       " 47,\n",
       " 48,\n",
       " 49,\n",
       " 50,\n",
       " 51,\n",
       " 52,\n",
       " 53,\n",
       " 54,\n",
       " 55,\n",
       " 56,\n",
       " 57,\n",
       " 58,\n",
       " 59,\n",
       " 60,\n",
       " 61,\n",
       " 62,\n",
       " 63,\n",
       " 64,\n",
       " 65,\n",
       " 66,\n",
       " 67,\n",
       " 68,\n",
       " 69,\n",
       " 70,\n",
       " 71,\n",
       " 72,\n",
       " 73,\n",
       " 74,\n",
       " 75,\n",
       " 76,\n",
       " 77,\n",
       " 78,\n",
       " 79,\n",
       " 80,\n",
       " 81,\n",
       " 82,\n",
       " 83,\n",
       " 84,\n",
       " 85,\n",
       " 86,\n",
       " 87,\n",
       " 88,\n",
       " 89,\n",
       " 90,\n",
       " 91,\n",
       " 92,\n",
       " 93,\n",
       " 94,\n",
       " 95,\n",
       " 96,\n",
       " 97,\n",
       " 98,\n",
       " 99]"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(range(0,100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 6, 8]"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(range(0,10,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[5, 4, 3, 2]"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(range(5,1,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "range??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'negative'"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Non-negative' if x>5 else 'negative'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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